The HIV/AIDS epidemic has affected millions of individuals worldwide over the past 30 years. Although there is currently no cure for HIV/AIDS, significant pharmacological advances in the treatment of HIV/AIDS have been developed, which has greatly extended the life expectancy and quality of life for individuals living with the diseas. Specifically, since 1996 antiretroviral (ARV) medication has been the standard of care in the United States, reducing the production of HIV viral particles in the body, as well as restoring the host body's immunological functioning. However, in order for (ARV) medication to be effective, a nearly 100% medication dose adherence rate is required. Individuals infected with HIV/AIDS on ARV medication regimens who are not adherent pose a significant public health risk as they are (a) at greater risk for disease progression; (b) more likely to be resistant to ARV medication treatment in the future; and (c) are more likely to transmit the virus to the general public, as wel as transmit mutated strains of the disease, which have a poorer response to ARV treatment. Adolescents and individuals from racial/ethnic minority backgrounds have been documented to have poor ARV adherence. Although prior studies have identified psychiatric illness and substance abuse to be strong predictors of ARV adherence, there is little research that examines the predictors of adherence among young adult and adolescent African American males, a demographic group at great risk for both HIV infection and ARV non-adherence. Therefore the objectives of the current study are to (a) identify the strongest predictors of ART adherence among African American adolescent and young adult males (<24 years) behaviorally infected with HIV; (b) to create a classification tree analysis model of adherence that maximizes classification accuracy for adherence and non-adherence; and (c) to identify the protective and risk factors that can be incorporated into intervention and prevention programs that increase ARV adherence. For the purpose of this study, a subsample of 790 African American males (<24 years) behaviorally-infected with HIV, who participated in the Adolescent Trials Network for HIV/AIDS Interventions (ATN) 086 protocol in 2010-2011, will be investigated using an exploratory multivariate analysis technique known as Optimal Data Analysis (ODA). ODA will allow the identification of the strongest predictor of adherence among a plethora of demographic, psychosocial, and biomedical data without increasing error. In addition, a classification tree analysis model will be created highlighting the pathways to adherence and non-adherence among African American males behaviorally-infected with HIV.